Overview

Dataset statistics

Number of variables11
Number of observations320772
Missing cells1001655
Missing cells (%)28.4%
Duplicate rows25853
Duplicate rows (%)8.1%
Total size in memory26.9 MiB
Average record size in memory88.0 B

Variable types

Numeric11

Alerts

Dataset has 25853 (8.1%) duplicate rowsDuplicates
salt_100g is highly overall correlated with sodium_100gHigh correlation
sodium_100g is highly overall correlated with salt_100gHigh correlation
fat_100g is highly overall correlated with energy_100g and 3 other fieldsHigh correlation
saturated_fat_100g is highly overall correlated with energy_100g and 3 other fieldsHigh correlation
nutrition_score_uk_100g is highly overall correlated with energy_100g and 3 other fieldsHigh correlation
nutrition_score_fr_100g is highly overall correlated with energy_100g and 3 other fieldsHigh correlation
energy_100g is highly overall correlated with fat_100g and 3 other fieldsHigh correlation
fiber_100g is highly overall correlated with sugars_100g and 1 other fieldsHigh correlation
sugars_100g is highly overall correlated with fiber_100g and 1 other fieldsHigh correlation
energy_100g has 59659 (18.6%) missing valuesMissing
salt_100g has 65262 (20.3%) missing valuesMissing
sodium_100g has 65309 (20.4%) missing valuesMissing
fiber_100g has 119886 (37.4%) missing valuesMissing
additives_n has 71833 (22.4%) missing valuesMissing
sugars_100g has 75801 (23.6%) missing valuesMissing
fat_100g has 76881 (24.0%) missing valuesMissing
saturated_fat_100g has 91218 (28.4%) missing valuesMissing
nutrition_score_uk_100g has 99562 (31.0%) missing valuesMissing
nutrition_score_fr_100g has 99562 (31.0%) missing valuesMissing
cholesterol_100g has 176682 (55.1%) missing valuesMissing
energy_100g is highly skewed (γ1 = 491.0039771)Skewed
salt_100g is highly skewed (γ1 = 493.5037928)Skewed
sodium_100g is highly skewed (γ1 = 493.458469)Skewed
fiber_100g is highly skewed (γ1 = 363.5478054)Skewed
cholesterol_100g is highly skewed (γ1 = 221.1178099)Skewed
energy_100g has 8909 (2.8%) zerosZeros
salt_100g has 34174 (10.7%) zerosZeros
sodium_100g has 34131 (10.6%) zerosZeros
fiber_100g has 68833 (21.5%) zerosZeros
additives_n has 94259 (29.4%) zerosZeros
sugars_100g has 37077 (11.6%) zerosZeros
fat_100g has 64504 (20.1%) zerosZeros
saturated_fat_100g has 68736 (21.4%) zerosZeros
nutrition_score_uk_100g has 13588 (4.2%) zerosZeros
nutrition_score_fr_100g has 12763 (4.0%) zerosZeros
cholesterol_100g has 89441 (27.9%) zerosZeros

Reproduction

Analysis started2024-06-07 15:43:35.174166
Analysis finished2024-06-07 15:44:02.450107
Duration27.28 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

energy_100g
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct3997
Distinct (%)1.5%
Missing59659
Missing (%)18.6%
Infinite0
Infinite (%)0.0%
Mean1141.9146
Minimum0
Maximum3251373
Zeros8909
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-06-07T17:44:02.547847image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile71
Q1377
median1100
Q31674
95-th percentile2389
Maximum3251373
Range3251373
Interquartile range (IQR)1297

Descriptive statistics

Standard deviation6447.1541
Coefficient of variation (CV)5.6459161
Kurtosis247388.17
Mean1141.9146
Median Absolute Deviation (MAD)657
Skewness491.00398
Sum2.9816875 × 108
Variance41565796
MonotonicityNot monotonic
2024-06-07T17:44:02.684454image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8909
 
2.8%
2092 5075
 
1.6%
1674 4012
 
1.3%
1494 3916
 
1.2%
1644 3282
 
1.0%
1393 3225
 
1.0%
1046 2945
 
0.9%
1569 2825
 
0.9%
1795 2350
 
0.7%
1197 2314
 
0.7%
Other values (3987) 222260
69.3%
(Missing) 59659
 
18.6%
ValueCountFrequency (%)
0 8909
2.8%
0.02 1
 
< 0.1%
0.42 1
 
< 0.1%
0.48 1
 
< 0.1%
0.6 1
 
< 0.1%
0.8 7
 
< 0.1%
0.9 4
 
< 0.1%
0.92 4
 
< 0.1%
1 50
 
< 0.1%
1.1 1
 
< 0.1%
ValueCountFrequency (%)
3251373 1
< 0.1%
231199 1
< 0.1%
182764 1
< 0.1%
110579 1
< 0.1%
94140 1
< 0.1%
87217 1
< 0.1%
69292 1
< 0.1%
26861 1
< 0.1%
22000 1
< 0.1%
18700 1
< 0.1%

salt_100g
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct5586
Distinct (%)2.2%
Missing65262
Missing (%)20.3%
Infinite0
Infinite (%)0.0%
Mean2.0286239
Minimum0
Maximum64312.8
Zeros34174
Zeros (%)10.7%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-06-07T17:44:02.819118image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0635
median0.58166
Q31.37414
95-th percentile4.064
Maximum64312.8
Range64312.8
Interquartile range (IQR)1.31064

Descriptive statistics

Standard deviation128.26945
Coefficient of variation (CV)63.229784
Kurtosis247314.47
Mean2.0286239
Median Absolute Deviation (MAD)0.55666
Skewness493.50379
Sum518333.71
Variance16453.053
MonotonicityNot monotonic
2024-06-07T17:44:02.952763image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34174
 
10.7%
0.01 3692
 
1.2%
0.1 3467
 
1.1%
1 2231
 
0.7%
0.0254 2093
 
0.7%
1.27 1941
 
0.6%
1.63322 1825
 
0.6%
0.127 1779
 
0.6%
0.03 1636
 
0.5%
1.3 1551
 
0.5%
Other values (5576) 201121
62.7%
(Missing) 65262
 
20.3%
ValueCountFrequency (%)
0 34174
10.7%
5 × 10-81
 
< 0.1%
9.999999 × 10-82
 
< 0.1%
1 × 10-61
 
< 0.1%
5 × 10-61
 
< 0.1%
7.874 × 10-61
 
< 0.1%
1 × 10-55
 
< 0.1%
1.3 × 10-54
 
< 0.1%
2 × 10-51
 
< 0.1%
2.413 × 10-51
 
< 0.1%
ValueCountFrequency (%)
64312.8 1
< 0.1%
3556 1
< 0.1%
3048 1
< 0.1%
2452.41318 1
< 0.1%
2177.14322 1
< 0.1%
2032 1
< 0.1%
1799.16582 1
< 0.1%
1669.14322 1
< 0.1%
1318.38192 1
< 0.1%
1139.1519 1
< 0.1%

sodium_100g
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct5291
Distinct (%)2.1%
Missing65309
Missing (%)20.4%
Infinite0
Infinite (%)0.0%
Mean0.79881546
Minimum0
Maximum25320
Zeros34131
Zeros (%)10.6%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-06-07T17:44:03.087406image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.025
median0.229
Q30.541
95-th percentile1.6
Maximum25320
Range25320
Interquartile range (IQR)0.516

Descriptive statistics

Standard deviation50.504428
Coefficient of variation (CV)63.22415
Kurtosis247269.02
Mean0.79881546
Median Absolute Deviation (MAD)0.21915748
Skewness493.45847
Sum204067.79
Variance2550.6972
MonotonicityNot monotonic
2024-06-07T17:44:03.229995image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34131
 
10.6%
0.003937007874 3687
 
1.1%
0.03937007874 3451
 
1.1%
0.3937007874 2216
 
0.7%
0.01 2092
 
0.7%
0.5 1939
 
0.6%
0.01181102362 1927
 
0.6%
0.643 1848
 
0.6%
0.05 1779
 
0.6%
0.5118110236 1545
 
0.5%
Other values (5281) 200848
62.6%
(Missing) 65309
 
20.4%
ValueCountFrequency (%)
0 34131
10.6%
1.968503937 × 10-81
 
< 0.1%
3.93700748 × 10-82
 
< 0.1%
3.937007874 × 10-71
 
< 0.1%
1.968503937 × 10-61
 
< 0.1%
3.1 × 10-61
 
< 0.1%
3.937007874 × 10-65
 
< 0.1%
5.118110236 × 10-64
 
< 0.1%
7.874015748 × 10-61
 
< 0.1%
9.5 × 10-61
 
< 0.1%
ValueCountFrequency (%)
25320 1
< 0.1%
1400 1
< 0.1%
1200 1
< 0.1%
965.517 1
< 0.1%
857.143 1
< 0.1%
800 1
< 0.1%
708.333 1
< 0.1%
657.143 1
< 0.1%
519.048 1
< 0.1%
448.485 1
< 0.1%

fiber_100g
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1016
Distinct (%)0.5%
Missing119886
Missing (%)37.4%
Infinite0
Infinite (%)0.0%
Mean2.8621109
Minimum-6.7
Maximum5380
Zeros68833
Zeros (%)21.5%
Negative1
Negative (%)< 0.1%
Memory size2.4 MiB
2024-06-07T17:44:03.376602image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum-6.7
5-th percentile0
Q10
median1.5
Q33.6
95-th percentile10.5
Maximum5380
Range5386.7
Interquartile range (IQR)3.6

Descriptive statistics

Standard deviation12.867578
Coefficient of variation (CV)4.4958348
Kurtosis151802.73
Mean2.8621109
Median Absolute Deviation (MAD)1.5
Skewness363.54781
Sum574958.02
Variance165.57456
MonotonicityNot monotonic
2024-06-07T17:44:03.516229image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 68833
21.5%
3.6 8525
 
2.7%
3.3 3991
 
1.2%
1.8 3886
 
1.2%
0.8 3829
 
1.2%
7.1 3707
 
1.2%
2 3531
 
1.1%
1.6 3428
 
1.1%
0.5 3419
 
1.1%
1.2 3278
 
1.0%
Other values (1006) 94459
29.4%
(Missing) 119886
37.4%
ValueCountFrequency (%)
-6.7 1
 
< 0.1%
0 68833
21.5%
0.0001 2
 
< 0.1%
0.0002 1
 
< 0.1%
0.001 16
 
< 0.1%
0.002 3
 
< 0.1%
0.004 1
 
< 0.1%
0.00416 1
 
< 0.1%
0.005 2
 
< 0.1%
0.01 72
 
< 0.1%
ValueCountFrequency (%)
5380 1
 
< 0.1%
250 1
 
< 0.1%
178 1
 
< 0.1%
166.7 1
 
< 0.1%
100 10
< 0.1%
99 1
 
< 0.1%
94.8 1
 
< 0.1%
92.4 1
 
< 0.1%
90 1
 
< 0.1%
88 2
 
< 0.1%

additives_n
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)< 0.1%
Missing71833
Missing (%)22.4%
Infinite0
Infinite (%)0.0%
Mean1.9360245
Minimum0
Maximum31
Zeros94259
Zeros (%)29.4%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-06-07T17:44:03.644886image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile7
Maximum31
Range31
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.5020195
Coefficient of variation (CV)1.2923491
Kurtosis7.4179254
Mean1.9360245
Median Absolute Deviation (MAD)1
Skewness2.1753736
Sum481952
Variance6.2601014
MonotonicityNot monotonic
2024-06-07T17:44:03.956053image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 94259
29.4%
1 46509
14.5%
2 36520
 
11.4%
3 23680
 
7.4%
4 15243
 
4.8%
5 10935
 
3.4%
6 7290
 
2.3%
7 4702
 
1.5%
8 3359
 
1.0%
9 2194
 
0.7%
Other values (21) 4248
 
1.3%
(Missing) 71833
22.4%
ValueCountFrequency (%)
0 94259
29.4%
1 46509
14.5%
2 36520
 
11.4%
3 23680
 
7.4%
4 15243
 
4.8%
5 10935
 
3.4%
6 7290
 
2.3%
7 4702
 
1.5%
8 3359
 
1.0%
9 2194
 
0.7%
ValueCountFrequency (%)
31 4
 
< 0.1%
29 2
 
< 0.1%
28 2
 
< 0.1%
27 2
 
< 0.1%
26 3
 
< 0.1%
25 11
< 0.1%
24 10
 
< 0.1%
23 15
< 0.1%
22 27
< 0.1%
21 21
< 0.1%

sugars_100g
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct4068
Distinct (%)1.7%
Missing75801
Missing (%)23.6%
Infinite0
Infinite (%)0.0%
Mean16.003484
Minimum-17.86
Maximum3520
Zeros37077
Zeros (%)11.6%
Negative7
Negative (%)< 0.1%
Memory size2.4 MiB
2024-06-07T17:44:04.097673image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum-17.86
5-th percentile0
Q11.3
median5.71
Q324
95-th percentile62.5
Maximum3520
Range3537.86
Interquartile range (IQR)22.7

Descriptive statistics

Standard deviation22.327284
Coefficient of variation (CV)1.3951515
Kurtosis2477.5694
Mean16.003484
Median Absolute Deviation (MAD)5.71
Skewness17.201619
Sum3920389.4
Variance498.50763
MonotonicityNot monotonic
2024-06-07T17:44:04.272207image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37077
 
11.6%
3.57 7148
 
2.2%
0.5 4589
 
1.4%
3.33 3706
 
1.2%
1 2666
 
0.8%
20 2347
 
0.7%
6.67 2269
 
0.7%
10 2192
 
0.7%
50 2129
 
0.7%
2 2042
 
0.6%
Other values (4058) 178806
55.7%
(Missing) 75801
23.6%
ValueCountFrequency (%)
-17.86 1
 
< 0.1%
-6.67 1
 
< 0.1%
-6.25 1
 
< 0.1%
-3.57 1
 
< 0.1%
-1.2 1
 
< 0.1%
-0.8 1
 
< 0.1%
-0.1 1
 
< 0.1%
0 37077
11.6%
0.0001 8
 
< 0.1%
0.0005 1
 
< 0.1%
ValueCountFrequency (%)
3520 1
 
< 0.1%
166.67 1
 
< 0.1%
134 1
 
< 0.1%
110.71 1
 
< 0.1%
105 1
 
< 0.1%
104 1
 
< 0.1%
103.5 4
 
< 0.1%
103 1
 
< 0.1%
100.8 1
 
< 0.1%
100 1011
0.3%

fat_100g
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct3378
Distinct (%)1.4%
Missing76881
Missing (%)24.0%
Infinite0
Infinite (%)0.0%
Mean12.730379
Minimum0
Maximum714.29
Zeros64504
Zeros (%)20.1%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-06-07T17:44:04.426397image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q320
95-th percentile46.43
Maximum714.29
Range714.29
Interquartile range (IQR)20

Descriptive statistics

Standard deviation17.578747
Coefficient of variation (CV)1.3808503
Kurtosis17.184558
Mean12.730379
Median Absolute Deviation (MAD)5
Skewness2.4647045
Sum3104824.8
Variance309.01234
MonotonicityNot monotonic
2024-06-07T17:44:04.575996image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 64504
20.1%
25 3409
 
1.1%
0.5 3202
 
1.0%
32.14 2981
 
0.9%
20 2688
 
0.8%
1.79 2528
 
0.8%
28.57 2460
 
0.8%
0.1 2437
 
0.8%
21.43 2411
 
0.8%
10 2284
 
0.7%
Other values (3368) 154987
48.3%
(Missing) 76881
24.0%
ValueCountFrequency (%)
0 64504
20.1%
0.0001 2
 
< 0.1%
0.000133 1
 
< 0.1%
0.001 1
 
< 0.1%
0.003 1
 
< 0.1%
0.004 2
 
< 0.1%
0.005 3
 
< 0.1%
0.007 1
 
< 0.1%
0.01 43
 
< 0.1%
0.012 2
 
< 0.1%
ValueCountFrequency (%)
714.29 1
 
< 0.1%
380 1
 
< 0.1%
105 1
 
< 0.1%
101 1
 
< 0.1%
100 1288
0.4%
99.9 16
 
< 0.1%
99.85 1
 
< 0.1%
99.82 1
 
< 0.1%
99.8 17
 
< 0.1%
99.7 5
 
< 0.1%

saturated_fat_100g
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct2197
Distinct (%)1.0%
Missing91218
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean5.1299323
Minimum0
Maximum550
Zeros68736
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-06-07T17:44:04.712658image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.79
Q37.14
95-th percentile20
Maximum550
Range550
Interquartile range (IQR)7.14

Descriptive statistics

Standard deviation8.0142381
Coefficient of variation (CV)1.5622503
Kurtosis116.64216
Mean5.1299323
Median Absolute Deviation (MAD)1.79
Skewness4.8175969
Sum1177596.5
Variance64.228013
MonotonicityNot monotonic
2024-06-07T17:44:04.843309image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 68736
21.4%
0.1 5355
 
1.7%
3.57 3487
 
1.1%
0.5 3302
 
1.0%
7.14 2880
 
0.9%
0.2 2601
 
0.8%
1 2444
 
0.8%
0.3 2335
 
0.7%
3.33 2213
 
0.7%
1.79 2190
 
0.7%
Other values (2187) 134011
41.8%
(Missing) 91218
28.4%
ValueCountFrequency (%)
0 68736
21.4%
0.0001 11
 
< 0.1%
0.001 30
 
< 0.1%
0.002 10
 
< 0.1%
0.003 4
 
< 0.1%
0.0032 1
 
< 0.1%
0.004 3
 
< 0.1%
0.005 11
 
< 0.1%
0.006 2
 
< 0.1%
0.00667 1
 
< 0.1%
ValueCountFrequency (%)
550 1
 
< 0.1%
210 1
 
< 0.1%
175.38 1
 
< 0.1%
100 12
< 0.1%
99.9 1
 
< 0.1%
99 2
 
< 0.1%
98 1
 
< 0.1%
96 2
 
< 0.1%
95.5 1
 
< 0.1%
95 5
< 0.1%

nutrition_score_uk_100g
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct55
Distinct (%)< 0.1%
Missing99562
Missing (%)31.0%
Infinite0
Infinite (%)0.0%
Mean9.0580489
Minimum-15
Maximum40
Zeros13588
Zeros (%)4.2%
Negative37361
Negative (%)11.6%
Memory size2.4 MiB
2024-06-07T17:44:04.967975image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum-15
5-th percentile-5
Q11
median9
Q316
95-th percentile24
Maximum40
Range55
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.1835893
Coefficient of variation (CV)1.0138595
Kurtosis-1.0755201
Mean9.0580489
Median Absolute Deviation (MAD)8
Skewness0.1320062
Sum2003731
Variance84.338312
MonotonicityNot monotonic
2024-06-07T17:44:05.110566image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 13588
 
4.2%
1 11932
 
3.7%
2 11083
 
3.5%
14 10689
 
3.3%
-1 8827
 
2.8%
13 8409
 
2.6%
12 8239
 
2.6%
11 8093
 
2.5%
3 7620
 
2.4%
20 7390
 
2.3%
Other values (45) 125340
39.1%
(Missing) 99562
31.0%
ValueCountFrequency (%)
-15 1
 
< 0.1%
-14 5
 
< 0.1%
-13 23
 
< 0.1%
-12 46
 
< 0.1%
-11 90
 
< 0.1%
-10 157
 
< 0.1%
-9 315
 
0.1%
-8 602
 
0.2%
-7 963
 
0.3%
-6 4926
1.5%
ValueCountFrequency (%)
40 3
 
< 0.1%
38 1
 
< 0.1%
37 2
 
< 0.1%
36 17
 
< 0.1%
35 34
 
< 0.1%
34 20
 
< 0.1%
33 101
< 0.1%
32 64
 
< 0.1%
31 76
 
< 0.1%
30 192
0.1%

nutrition_score_fr_100g
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct55
Distinct (%)< 0.1%
Missing99562
Missing (%)31.0%
Infinite0
Infinite (%)0.0%
Mean9.165535
Minimum-15
Maximum40
Zeros12763
Zeros (%)4.0%
Negative35706
Negative (%)11.1%
Memory size2.4 MiB
2024-06-07T17:44:05.254210image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum-15
5-th percentile-5
Q11
median10
Q316
95-th percentile24
Maximum40
Range55
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.0559029
Coefficient of variation (CV)0.98803866
Kurtosis-1.0188856
Mean9.165535
Median Absolute Deviation (MAD)8
Skewness0.11483636
Sum2027508
Variance82.009378
MonotonicityNot monotonic
2024-06-07T17:44:05.390817image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12763
 
4.0%
1 11268
 
3.5%
14 11253
 
3.5%
2 10604
 
3.3%
13 8827
 
2.8%
-1 8804
 
2.7%
12 8658
 
2.7%
11 8653
 
2.7%
3 7857
 
2.4%
15 7529
 
2.3%
Other values (45) 124994
39.0%
(Missing) 99562
31.0%
ValueCountFrequency (%)
-15 1
 
< 0.1%
-14 5
 
< 0.1%
-13 23
 
< 0.1%
-12 46
 
< 0.1%
-11 90
 
< 0.1%
-10 159
 
< 0.1%
-9 315
 
0.1%
-8 601
 
0.2%
-7 950
 
0.3%
-6 4925
1.5%
ValueCountFrequency (%)
40 4
 
< 0.1%
38 1
 
< 0.1%
37 3
 
< 0.1%
36 17
 
< 0.1%
35 36
 
< 0.1%
34 20
 
< 0.1%
33 105
< 0.1%
32 73
 
< 0.1%
31 79
 
< 0.1%
30 207
0.1%

cholesterol_100g
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct537
Distinct (%)0.4%
Missing176682
Missing (%)55.1%
Infinite0
Infinite (%)0.0%
Mean0.020071383
Minimum0
Maximum95.238
Zeros89441
Zeros (%)27.9%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-06-07T17:44:05.527487image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.02
95-th percentile0.09
Maximum95.238
Range95.238
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.35806161
Coefficient of variation (CV)17.839408
Kurtosis51631.976
Mean0.020071383
Median Absolute Deviation (MAD)0
Skewness221.11781
Sum2892.0856
Variance0.12820811
MonotonicityNot monotonic
2024-06-07T17:44:05.667106image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 89441
27.9%
0.071 2462
 
0.8%
0.107 2237
 
0.7%
0.012 1909
 
0.6%
0.089 1664
 
0.5%
0.054 1651
 
0.5%
0.018 1591
 
0.5%
0.004 1503
 
0.5%
0.036 1386
 
0.4%
0.008 1209
 
0.4%
Other values (527) 39037
 
12.2%
(Missing) 176682
55.1%
ValueCountFrequency (%)
0 89441
27.9%
4.5 × 10-51
 
< 0.1%
7.1 × 10-51
 
< 0.1%
0.0001 5
 
< 0.1%
0.0002 5
 
< 0.1%
0.0004 1
 
< 0.1%
0.000416 1
 
< 0.1%
0.00046 1
 
< 0.1%
0.0005 2
 
< 0.1%
0.0008 1
 
< 0.1%
ValueCountFrequency (%)
95.238 1
< 0.1%
70.588 1
< 0.1%
62.5 1
< 0.1%
13.846 1
< 0.1%
10.9 1
< 0.1%
1.58 1
< 0.1%
1.291 1
< 0.1%
1.25 1
< 0.1%
1.081 1
< 0.1%
0.996 1
< 0.1%

Interactions

2024-06-07T17:44:00.161206image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:47.097146image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:48.503384image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:49.782964image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:51.037607image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:52.261333image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:53.639648image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:54.955128image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:56.227724image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:57.646928image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:58.889604image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:44:00.268915image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:47.225803image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:48.625059image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:49.902643image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:51.151303image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:52.502689image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:53.762318image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:55.076802image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:56.344412image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:57.766609image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:59.007289image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:44:00.380616image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:47.348473image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-06-07T17:43:51.261009image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:52.619378image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:53.882995image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:55.197480image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:56.469079image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-06-07T17:43:59.122981image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-06-07T17:43:49.325187image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-06-07T17:44:01.058803image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:48.061567image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:49.442873image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:50.709485image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:51.936203image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:53.307534image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-06-07T17:43:55.891624image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:57.171202image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:58.565471image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:59.831086image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:44:01.163522image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:48.177258image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:49.557570image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:50.821187image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:52.045912image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:53.418240image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:54.730728image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:56.009308image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:57.282902image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:58.678169image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:59.946776image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:44:01.276221image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:48.387701image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:49.668270image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:50.929895image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:52.153623image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:53.527945image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:54.842428image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:56.117021image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:57.536224image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:43:58.780895image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-07T17:44:00.053490image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Correlations

2024-06-07T17:44:05.758861image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
energy_100gsalt_100gsodium_100gfiber_100gadditives_nsugars_100gfat_100gsaturated_fat_100gnutrition_score_uk_100gnutrition_score_fr_100gcholesterol_100g
energy_100g1.000-0.001-0.0010.077-0.0030.0570.0940.0740.0700.0680.005
salt_100g-0.0011.0001.000-0.000-0.0010.000-0.004-0.0020.0070.0070.113
sodium_100g-0.0011.0001.000-0.000-0.0010.000-0.004-0.0020.0070.0070.113
fiber_100g0.077-0.000-0.0001.000-0.0510.3450.1360.155-0.045-0.047-0.024
additives_n-0.003-0.001-0.001-0.0511.0000.136-0.121-0.0530.1630.167-0.005
sugars_100g0.0570.0000.0000.3450.1361.000-0.0470.1570.4320.442-0.017
fat_100g0.094-0.004-0.0040.136-0.121-0.0471.0000.6890.5920.5680.022
saturated_fat_100g0.074-0.002-0.0020.155-0.0530.1570.6891.0000.6410.6240.044
nutrition_score_uk_100g0.0700.0070.007-0.0450.1630.4320.5920.6411.0000.9860.031
nutrition_score_fr_100g0.0680.0070.007-0.0470.1670.4420.5680.6240.9861.0000.031
cholesterol_100g0.0050.1130.113-0.024-0.005-0.0170.0220.0440.0310.0311.000
2024-06-07T17:44:05.906465image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
energy_100gsalt_100gsodium_100gfiber_100gadditives_nsugars_100gfat_100gsaturated_fat_100gnutrition_score_uk_100gnutrition_score_fr_100gcholesterol_100g
energy_100g1.0000.1220.1220.3320.0220.2930.7370.6160.6590.6390.004
salt_100g0.1221.0001.000-0.0510.142-0.2780.2980.1870.3750.3490.244
sodium_100g0.1221.0001.000-0.0510.142-0.2780.2980.1870.3750.3490.244
fiber_100g0.332-0.051-0.0511.000-0.1770.0910.1900.016-0.205-0.212-0.397
additives_n0.0220.1420.142-0.1771.0000.213-0.0440.0360.2270.2330.105
sugars_100g0.293-0.278-0.2780.0910.2131.000-0.0450.0700.3600.383-0.155
fat_100g0.7370.2980.2980.190-0.044-0.0451.0000.8670.6430.6180.317
saturated_fat_100g0.6160.1870.1870.0160.0360.0700.8671.0000.7050.6830.475
nutrition_score_uk_100g0.6590.3750.375-0.2050.2270.3600.6430.7051.0000.9850.299
nutrition_score_fr_100g0.6390.3490.349-0.2120.2330.3830.6180.6830.9851.0000.299
cholesterol_100g0.0040.2440.244-0.3970.105-0.1550.3170.4750.2990.2991.000
2024-06-07T17:44:06.051085image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
energy_100gsalt_100gsodium_100gfiber_100gadditives_nsugars_100gfat_100gsaturated_fat_100gnutrition_score_uk_100gnutrition_score_fr_100gcholesterol_100g
energy_100g1.0000.0880.0880.2300.0150.2010.5870.4540.4750.4580.015
salt_100g0.0881.0001.000-0.0340.104-0.1910.2190.1340.2620.2430.194
sodium_100g0.0881.0001.000-0.0340.104-0.1910.2190.1340.2620.2430.194
fiber_100g0.230-0.034-0.0341.000-0.1370.0690.1410.014-0.152-0.157-0.322
additives_n0.0150.1040.104-0.1371.0000.157-0.0360.0260.1660.1700.085
sugars_100g0.201-0.191-0.1910.0690.1571.000-0.0280.0550.2620.277-0.119
fat_100g0.5870.2190.2190.141-0.036-0.0281.0000.7120.4640.4430.261
saturated_fat_100g0.4540.1340.1340.0140.0260.0550.7121.0000.5400.5190.396
nutrition_score_uk_100g0.4750.2620.262-0.1520.1660.2620.4640.5401.0000.9670.226
nutrition_score_fr_100g0.4580.2430.243-0.1570.1700.2770.4430.5190.9671.0000.226
cholesterol_100g0.0150.1940.194-0.3220.085-0.1190.2610.3960.2260.2261.000
2024-06-07T17:44:06.204668image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
energy_100gsalt_100gsodium_100gfiber_100gadditives_nsugars_100gfat_100gsaturated_fat_100gnutrition_score_uk_100gnutrition_score_fr_100gcholesterol_100g
energy_100g1.0000.0000.0000.0000.0000.0000.0000.0000.0000.000NaN
salt_100g0.0001.0000.707NaN0.0000.0000.0000.0000.0000.000NaN
sodium_100g0.0000.7071.000NaN0.0000.0000.0000.0000.0000.000NaN
fiber_100g0.000NaNNaN1.0000.0000.707NaN1.0000.0100.010NaN
additives_n0.0000.0000.0000.0001.0000.0000.0580.0220.1870.1820.000
sugars_100g0.0000.0000.0000.7070.0001.000NaN1.0000.0080.008NaN
fat_100g0.0000.0000.000NaN0.058NaN1.0000.7050.2070.1790.000
saturated_fat_100g0.0000.0000.0001.0000.0221.0000.7051.0000.1510.1480.000
nutrition_score_uk_100g0.0000.0000.0000.0100.1870.0080.2070.1511.0001.0000.000
nutrition_score_fr_100g0.0000.0000.0000.0100.1820.0080.1790.1481.0001.0000.000
cholesterol_100gNaNNaNNaNNaN0.000NaN0.0000.0000.0000.0001.000
2024-06-07T17:44:06.352273image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
additives_ncholesterol_100genergy_100gfat_100gfiber_100gnutrition_score_fr_100gnutrition_score_uk_100gsalt_100gsaturated_fat_100gsodium_100gsugars_100g
additives_n1.0000.1050.022-0.044-0.1770.2330.2270.1420.0360.1420.213
cholesterol_100g0.1051.0000.0040.317-0.3970.2990.2990.2440.4750.244-0.155
energy_100g0.0220.0041.0000.7370.3320.6390.6590.1220.6160.1220.293
fat_100g-0.0440.3170.7371.0000.1900.6180.6430.2980.8670.298-0.045
fiber_100g-0.177-0.3970.3320.1901.000-0.212-0.205-0.0510.016-0.0510.091
nutrition_score_fr_100g0.2330.2990.6390.618-0.2121.0000.9850.3490.6830.3490.383
nutrition_score_uk_100g0.2270.2990.6590.643-0.2050.9851.0000.3750.7050.3750.360
salt_100g0.1420.2440.1220.298-0.0510.3490.3751.0000.1871.000-0.278
saturated_fat_100g0.0360.4750.6160.8670.0160.6830.7050.1871.0000.1870.070
sodium_100g0.1420.2440.1220.298-0.0510.3490.3751.0000.1871.000-0.278
sugars_100g0.213-0.1550.293-0.0450.0910.3830.360-0.2780.070-0.2781.000

Missing values

2024-06-07T17:44:01.407868image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-06-07T17:44:01.699090image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

energy_100gsalt_100gsodium_100gfiber_100gadditives_nsugars_100gfat_100gsaturated_fat_100gnutrition_score_uk_100gnutrition_score_fr_100gcholesterol_100g
0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
12243.00.000000.0003.60.014.2928.5728.5714.014.00.018
21941.00.635000.2507.10.017.8617.860.000.00.00.000
32540.01.224280.4827.10.03.5757.145.3612.012.0NaN
41552.0NaNNaN5.70.0NaN1.43NaNNaNNaNNaN
51933.0NaNNaN7.70.011.5418.271.92NaNNaNNaN
61490.0NaNNaNNaN0.0NaNNaNNaNNaNNaNNaN
71833.00.139700.0559.42.015.6218.754.697.07.0NaN
82406.0NaNNaN7.50.042.5037.5022.50NaNNaNNaN
93586.0NaNNaNNaN0.0NaN100.007.14NaNNaNNaN
energy_100gsalt_100gsodium_100gfiber_100gadditives_nsugars_100gfat_100gsaturated_fat_100gnutrition_score_uk_100gnutrition_score_fr_100gcholesterol_100g
320762NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
32076321.00.02540.010.20.00.50.20.20.02.0NaN
320764NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
320765NaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaN
320766NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
320767NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
3207680.00.00000.000.00.00.00.00.00.00.00.0
320769NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
320770NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
3207712092.00.00000.00NaN7.00.00.0NaNNaNNaNNaN

Duplicate rows

Most frequently occurring

energy_100gsalt_100gsodium_100gfiber_100gadditives_nsugars_100gfat_100gsaturated_fat_100gnutrition_score_uk_100gnutrition_score_fr_100gcholesterol_100g# duplicates
25852NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN44597
25761NaNNaNNaNNaN0.0NaNNaNNaNNaNNaNNaN9268
25780NaNNaNNaNNaN1.0NaNNaNNaNNaNNaNNaN1506
25789NaNNaNNaNNaN2.0NaNNaNNaNNaNNaNNaN900
510.00.00.0NaN0.0NaN0.00NaNNaNNaNNaN856
440.00.00.0NaN0.00.000.00NaNNaNNaNNaN663
254333347.00.00.0NaN0.0NaN93.3313.33NaNNaN0.0577
25792NaNNaNNaNNaN3.0NaNNaNNaNNaNNaNNaN547
161711494.00.00.03.62.03.571.790.00-6.0-6.00.0485
25796NaNNaNNaNNaN4.0NaNNaNNaNNaNNaNNaN337